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| <section id="using-the-sql-api"> |
| <h1>Using the SQL API<a class="headerlink" href="#using-the-sql-api" title="Link to this heading">#</a></h1> |
| <p>DataFusion has a full SQL API that allows you to interact with DataFusion using |
| SQL query strings. The simplest way to use the SQL API is to use the |
| <a class="reference external" href="https://docs.rs/datafusion/latest/datafusion/execution/context/struct.SessionContext.html"><code class="docutils literal notranslate"><span class="pre">SessionContext</span></code></a> struct which provides the highest-level API for executing SQL |
| queries.</p> |
| <p>To use SQL, you first register your data as a table and then run queries |
| using the <a class="reference external" href="https://docs.rs/datafusion/latest/datafusion/execution/context/struct.SessionContext.html#method.sql"><code class="docutils literal notranslate"><span class="pre">SessionContext::sql</span></code></a> method. For lower level control such as |
| preventing DDL, you can use <a class="reference external" href="https://docs.rs/datafusion/latest/datafusion/execution/context/struct.SessionContext.html#method.sql_with_options"><code class="docutils literal notranslate"><span class="pre">SessionContext::sql_with_options</span></code></a> or the |
| <a class="reference external" href="https://docs.rs/datafusion/latest/datafusion/execution/session_state/struct.SessionState.html"><code class="docutils literal notranslate"><span class="pre">SessionState</span></code></a> APIs</p> |
| <section id="registering-data-sources-using-sessioncontext-register"> |
| <h2>Registering Data Sources using <code class="docutils literal notranslate"><span class="pre">SessionContext::register*</span></code><a class="headerlink" href="#registering-data-sources-using-sessioncontext-register" title="Link to this heading">#</a></h2> |
| <p>The <code class="docutils literal notranslate"><span class="pre">SessionContext::register*</span></code> methods tell DataFusion the name of |
| the source and how to read data. Once registered, you can execute SQL queries |
| using the <a class="reference external" href="https://docs.rs/datafusion/latest/datafusion/execution/context/struct.SessionContext.html#method.sql"><code class="docutils literal notranslate"><span class="pre">SessionContext::sql</span></code></a> method referring to your data source as a table.</p> |
| <p>The <a class="reference external" href="https://docs.rs/datafusion/latest/datafusion/execution/context/struct.SessionContext.html#method.sql"><code class="docutils literal notranslate"><span class="pre">SessionContext::sql</span></code></a> method returns a <code class="docutils literal notranslate"><span class="pre">DataFrame</span></code> for ease of |
| use. See the <a class="reference internal" href="using-the-dataframe-api.html"><span class="std std-doc">“Using the DataFrame API”</span></a> section for more information on how to |
| work with DataFrames.</p> |
| <section id="read-a-csv-file"> |
| <h3>Read a CSV File<a class="headerlink" href="#read-a-csv-file" title="Link to this heading">#</a></h3> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="k">use</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">error</span><span class="p">::</span><span class="nb">Result</span><span class="p">;</span> |
| <span class="k">use</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">prelude</span><span class="p">::</span><span class="o">*</span><span class="p">;</span> |
| <span class="k">use</span><span class="w"> </span><span class="n">arrow</span><span class="p">::</span><span class="n">record_batch</span><span class="p">::</span><span class="n">RecordBatch</span><span class="p">;</span> |
| |
| <span class="cp">#[tokio::main]</span> |
| <span class="k">async</span><span class="w"> </span><span class="k">fn</span><span class="w"> </span><span class="nf">main</span><span class="p">()</span><span class="w"> </span><span class="p">-></span><span class="w"> </span><span class="nb">Result</span><span class="o"><</span><span class="p">()</span><span class="o">></span><span class="w"> </span><span class="p">{</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">SessionContext</span><span class="p">::</span><span class="n">new</span><span class="p">();</span> |
| <span class="w"> </span><span class="c1">// register the "example" table</span> |
| <span class="w"> </span><span class="n">ctx</span><span class="p">.</span><span class="n">register_csv</span><span class="p">(</span><span class="s">"example"</span><span class="p">,</span><span class="w"> </span><span class="s">"tests/data/example.csv"</span><span class="p">,</span><span class="w"> </span><span class="n">CsvReadOptions</span><span class="p">::</span><span class="n">new</span><span class="p">()).</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| <span class="w"> </span><span class="c1">// create a plan to run a SQL query</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">df</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">ctx</span><span class="p">.</span><span class="n">sql</span><span class="p">(</span><span class="s">"SELECT a, min(b) FROM example WHERE a <= b GROUP BY a LIMIT 100"</span><span class="p">).</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| <span class="w"> </span><span class="c1">// execute the plan and collect the results as Vec<RecordBatch></span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">results</span><span class="p">:</span><span class="w"> </span><span class="nb">Vec</span><span class="o"><</span><span class="n">RecordBatch</span><span class="o">></span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">df</span><span class="p">.</span><span class="n">collect</span><span class="p">().</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| <span class="w"> </span><span class="c1">// Use the assert_batches_eq macro to compare the results with expected output</span> |
| <span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">assert_batches_eq</span><span class="o">!</span><span class="p">(</span><span class="fm">vec!</span><span class="p">[</span> |
| <span class="w"> </span><span class="s">"+---+----------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| a | min(example.b) |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"+---+----------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| 1 | 2 |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"+---+----------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="p">],</span> |
| <span class="w"> </span><span class="o">&</span><span class="n">results</span> |
| <span class="w"> </span><span class="p">);</span> |
| <span class="w"> </span><span class="nb">Ok</span><span class="p">(())</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| </section> |
| <section id="read-an-apache-parquet-file"> |
| <h3>Read an Apache Parquet file<a class="headerlink" href="#read-an-apache-parquet-file" title="Link to this heading">#</a></h3> |
| <p>Similarly to CSV, you can register a Parquet file as a table using the <code class="docutils literal notranslate"><span class="pre">register_parquet</span></code> method.</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="k">use</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">error</span><span class="p">::</span><span class="nb">Result</span><span class="p">;</span> |
| <span class="k">use</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">prelude</span><span class="p">::</span><span class="o">*</span><span class="p">;</span> |
| <span class="cp">#[tokio::main]</span> |
| <span class="k">async</span><span class="w"> </span><span class="k">fn</span><span class="w"> </span><span class="nf">main</span><span class="p">()</span><span class="w"> </span><span class="p">-></span><span class="w"> </span><span class="nb">Result</span><span class="o"><</span><span class="p">()</span><span class="o">></span><span class="w"> </span><span class="p">{</span> |
| <span class="w"> </span><span class="c1">// create local session context</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">SessionContext</span><span class="p">::</span><span class="n">new</span><span class="p">();</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">testdata</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">test_util</span><span class="p">::</span><span class="n">parquet_test_data</span><span class="p">();</span> |
| |
| <span class="w"> </span><span class="c1">// register parquet file with the execution context</span> |
| <span class="w"> </span><span class="n">ctx</span><span class="p">.</span><span class="n">register_parquet</span><span class="p">(</span> |
| <span class="w"> </span><span class="s">"alltypes_plain"</span><span class="p">,</span> |
| <span class="w"> </span><span class="o">&</span><span class="fm">format!</span><span class="p">(</span><span class="s">"{testdata}/alltypes_plain.parquet"</span><span class="p">),</span> |
| <span class="w"> </span><span class="n">ParquetReadOptions</span><span class="p">::</span><span class="n">default</span><span class="p">(),</span> |
| <span class="w"> </span><span class="p">)</span> |
| <span class="w"> </span><span class="p">.</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| |
| <span class="w"> </span><span class="c1">// execute the query</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">df</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">ctx</span><span class="p">.</span><span class="n">sql</span><span class="p">(</span> |
| <span class="w"> </span><span class="s">"SELECT int_col, double_col, CAST(date_string_col as VARCHAR) \</span> |
| <span class="s"> FROM alltypes_plain \</span> |
| <span class="s"> WHERE id > 1 AND tinyint_col < double_col"</span><span class="p">,</span> |
| <span class="w"> </span><span class="p">).</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| |
| <span class="w"> </span><span class="c1">// execute the plan, and compare to the expected results</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">results</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">df</span><span class="p">.</span><span class="n">collect</span><span class="p">().</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| <span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">assert_batches_eq</span><span class="o">!</span><span class="p">(</span><span class="fm">vec!</span><span class="p">[</span> |
| <span class="w"> </span><span class="s">"+---------+------------+--------------------------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| int_col | double_col | alltypes_plain.date_string_col |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"+---------+------------+--------------------------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| 1 | 10.1 | 03/01/09 |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| 1 | 10.1 | 04/01/09 |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| 1 | 10.1 | 02/01/09 |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"+---------+------------+--------------------------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="p">],</span> |
| <span class="w"> </span><span class="o">&</span><span class="n">results</span> |
| <span class="w"> </span><span class="p">);</span> |
| <span class="w"> </span><span class="nb">Ok</span><span class="p">(())</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| </section> |
| <section id="read-an-apache-avro-file"> |
| <h3>Read an Apache Avro file<a class="headerlink" href="#read-an-apache-avro-file" title="Link to this heading">#</a></h3> |
| <p>DataFusion can also read Avro files using the <code class="docutils literal notranslate"><span class="pre">register_avro</span></code> method.</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="p">{</span> |
| <span class="k">use</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">arrow</span><span class="p">::</span><span class="n">util</span><span class="p">::</span><span class="n">pretty</span><span class="p">;</span> |
| <span class="k">use</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">error</span><span class="p">::</span><span class="nb">Result</span><span class="p">;</span> |
| <span class="k">use</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">prelude</span><span class="p">::</span><span class="o">*</span><span class="p">;</span> |
| |
| <span class="cp">#[tokio::main]</span> |
| <span class="k">async</span><span class="w"> </span><span class="k">fn</span><span class="w"> </span><span class="nf">main</span><span class="p">()</span><span class="w"> </span><span class="p">-></span><span class="w"> </span><span class="nb">Result</span><span class="o"><</span><span class="p">()</span><span class="o">></span><span class="w"> </span><span class="p">{</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">SessionContext</span><span class="p">::</span><span class="n">new</span><span class="p">();</span> |
| <span class="w"> </span><span class="c1">// find the path to the avro test files</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">testdata</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">test_util</span><span class="p">::</span><span class="n">arrow_test_data</span><span class="p">();</span> |
| <span class="w"> </span><span class="c1">// register avro file with the execution context</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">avro_file</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="o">&</span><span class="fm">format!</span><span class="p">(</span><span class="s">"{testdata}/avro/alltypes_plain.avro"</span><span class="p">);</span> |
| <span class="w"> </span><span class="n">ctx</span><span class="p">.</span><span class="n">register_avro</span><span class="p">(</span><span class="s">"alltypes_plain"</span><span class="p">,</span><span class="w"> </span><span class="n">avro_file</span><span class="p">,</span><span class="w"> </span><span class="n">AvroReadOptions</span><span class="p">::</span><span class="n">default</span><span class="p">()).</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| |
| <span class="w"> </span><span class="c1">// execute the query</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">df</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">ctx</span><span class="p">.</span><span class="n">sql</span><span class="p">(</span> |
| <span class="w"> </span><span class="s">"SELECT int_col, double_col, CAST(date_string_col as VARCHAR) \</span> |
| <span class="s"> FROM alltypes_plain \</span> |
| <span class="s"> WHERE id > 1 AND tinyint_col < double_col"</span> |
| <span class="w"> </span><span class="p">).</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| |
| <span class="w"> </span><span class="c1">// execute the plan, and compare to the expected results</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">results</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">df</span><span class="p">.</span><span class="n">collect</span><span class="p">().</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| <span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">assert_batches_eq</span><span class="o">!</span><span class="p">(</span><span class="fm">vec!</span><span class="p">[</span> |
| <span class="w"> </span><span class="s">"+---------+------------+--------------------------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| int_col | double_col | alltypes_plain.date_string_col |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"+---------+------------+--------------------------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| 1 | 10.1 | 03/01/09 |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| 1 | 10.1 | 04/01/09 |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| 1 | 10.1 | 02/01/09 |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"+---------+------------+--------------------------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="p">],</span> |
| <span class="w"> </span><span class="o">&</span><span class="n">results</span> |
| <span class="w"> </span><span class="p">);</span> |
| <span class="w"> </span><span class="nb">Ok</span><span class="p">(())</span> |
| <span class="p">}</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| </section> |
| </section> |
| <section id="reading-multiple-files-as-a-table"> |
| <h2>Reading Multiple Files as a table<a class="headerlink" href="#reading-multiple-files-as-a-table" title="Link to this heading">#</a></h2> |
| <p>It is also possible to read multiple files as a single table. This is done |
| with the ListingTableProvider which takes a list of file paths and reads them |
| as a single table, matching schemas as appropriate</p> |
| <p>Coming Soon</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span> |
| </pre></div> |
| </div> |
| </section> |
| <section id="using-create-external-table-to-register-data-sources-via-sql"> |
| <h2>Using <code class="docutils literal notranslate"><span class="pre">CREATE</span> <span class="pre">EXTERNAL</span> <span class="pre">TABLE</span></code> to register data sources via SQL<a class="headerlink" href="#using-create-external-table-to-register-data-sources-via-sql" title="Link to this heading">#</a></h2> |
| <p>You can also register files using SQL using the <a class="reference internal" href="../user-guide/sql/ddl.html#create-external-table"><span class="std std-ref"><code class="docutils literal notranslate"><span class="pre">CREATE</span> <span class="pre">EXTERNAL</span> <span class="pre">TABLE</span></code></span></a> |
| statement.</p> |
| <div class="highlight-rust notranslate"><div class="highlight"><pre><span></span><span class="k">use</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">error</span><span class="p">::</span><span class="nb">Result</span><span class="p">;</span> |
| <span class="k">use</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">prelude</span><span class="p">::</span><span class="o">*</span><span class="p">;</span> |
| <span class="cp">#[tokio::main]</span> |
| <span class="k">async</span><span class="w"> </span><span class="k">fn</span><span class="w"> </span><span class="nf">main</span><span class="p">()</span><span class="w"> </span><span class="p">-></span><span class="w"> </span><span class="nb">Result</span><span class="o"><</span><span class="p">()</span><span class="o">></span><span class="w"> </span><span class="p">{</span> |
| <span class="w"> </span><span class="c1">// create local session context</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">SessionContext</span><span class="p">::</span><span class="n">new</span><span class="p">();</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">testdata</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">test_util</span><span class="p">::</span><span class="n">parquet_test_data</span><span class="p">();</span> |
| |
| <span class="w"> </span><span class="c1">// register parquet file using SQL</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">ddl</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="fm">format!</span><span class="p">(</span> |
| <span class="w"> </span><span class="s">"CREATE EXTERNAL TABLE alltypes_plain \</span> |
| <span class="s"> STORED AS PARQUET LOCATION '{testdata}/alltypes_plain.parquet'"</span> |
| <span class="w"> </span><span class="p">);</span> |
| <span class="w"> </span><span class="n">ctx</span><span class="p">.</span><span class="n">sql</span><span class="p">(</span><span class="o">&</span><span class="n">ddl</span><span class="p">).</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| |
| <span class="w"> </span><span class="c1">// execute the query referring to the alltypes_plain table we just registered</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">df</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">ctx</span><span class="p">.</span><span class="n">sql</span><span class="p">(</span> |
| <span class="w"> </span><span class="s">"SELECT int_col, double_col, CAST(date_string_col as VARCHAR) \</span> |
| <span class="s"> FROM alltypes_plain \</span> |
| <span class="s"> WHERE id > 1 AND tinyint_col < double_col"</span><span class="p">,</span> |
| <span class="w"> </span><span class="p">).</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| |
| <span class="w"> </span><span class="c1">// execute the plan, and compare to the expected results</span> |
| <span class="w"> </span><span class="kd">let</span><span class="w"> </span><span class="n">results</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">df</span><span class="p">.</span><span class="n">collect</span><span class="p">().</span><span class="k">await</span><span class="o">?</span><span class="p">;</span> |
| <span class="w"> </span><span class="n">datafusion</span><span class="p">::</span><span class="n">assert_batches_eq</span><span class="o">!</span><span class="p">(</span><span class="fm">vec!</span><span class="p">[</span> |
| <span class="w"> </span><span class="s">"+---------+------------+--------------------------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| int_col | double_col | alltypes_plain.date_string_col |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"+---------+------------+--------------------------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| 1 | 10.1 | 03/01/09 |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| 1 | 10.1 | 04/01/09 |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"| 1 | 10.1 | 02/01/09 |"</span><span class="p">,</span> |
| <span class="w"> </span><span class="s">"+---------+------------+--------------------------------+"</span><span class="p">,</span> |
| <span class="w"> </span><span class="p">],</span> |
| <span class="w"> </span><span class="o">&</span><span class="n">results</span> |
| <span class="w"> </span><span class="p">);</span> |
| <span class="w"> </span><span class="nb">Ok</span><span class="p">(())</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
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| </section> |
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